1) La descarga del recurso depende de la página de origen
2) Para poder descargar el recurso, es necesario ser usuario registrado en Universia

Opción 1: Descargar recurso

Opción 2: Descargar recurso

Detalles del recurso


Scientic computing is an increasingly crucial component of research in various disciplines. Despite its potential, exploration of the results is an often laborious task, owing to excessively large and verbose datasets output by typical simulation runs. Several approaches have been proposed to analyze, classify, and simplify such data to facilitate an informative visualization and deeper understanding of the underlying system. However, traditional methods leave much room for improvement. In this article we investigate the visualization of large vector elds, departing from accustomed processing algorithms by casting vector eld simplication as a variational partitioning problem. Adopting an iterative strategy, we introduce the notion of vector ieproxiesln to minimize the distortion error of our simplifiation by clustering the dataset into multiple best-fitting characteristic regions. This error driven approach can be performed with respect to various similarity metrics, offering a convenient set of tools to design clear and succinct representations of high dimensional datasets. We illustrate the benefits of such tools through visualization experiments of three-dimensional vector fields.

Pertenece a

Caltech Authors  


McKenzie, Alexander -  Lombeyda, Santiago -  Desbrun, Mathieu - 

Id.: 54786426

Versión: 1.0

Estado: Final

Tipo:  application/pdf -  image/png - 

Tipo de recurso: Conference or Workshop Item  -  PeerReviewed  - 

Tipo de Interactividad: Expositivo

Nivel de Interactividad: muy bajo

Audiencia: Estudiante  -  Profesor  -  Autor  - 

Estructura: Atomic

Coste: no

Copyright: sí

Formatos:  application/pdf -  image/png - 

Requerimientos técnicos:  Browser: Any - 

Relación: [References] http://resolver.caltech.edu/CaltechCACR:2005.106
[References] http://authors.library.caltech.edu/28214/

Fecha de contribución: 27-dic-2012


* McKenzie, Alexander and Lombeyda, Santiago and Desbrun, Mathieu (2005) Vector Field Analysis and Visualization through Variational Clustering. In: Eurographics - IEEE VGTC Symposium on Visualization 2005, 1-3 June, 2005, Leeds, UK. (Submitted) http://resolver.caltech.edu/CaltechCACR:2005.106

Otros recursos del mismo autor(es)

  1. Variance-minimizing transport plans for inter-surface mapping We introduce an efficient computational method for generating dense and low distortion maps between ...
  2. Spectral Affine-Kernel Embeddings In this paper, we propose a controllable embedding method for high- and low-dimensional geometry pro...
  3. The Power of Orthogonal Duals (Invited Talk) Triangle meshes have found widespread acceptance in computer graphics as a simple, convenient, and v...
  4. Geometric Computational Electrodynamics with Variational Integrators and Discrete Differential Forms In this paper, we develop a structure-preserving discretization of the Lagrangian framework for elec...
  5. Numerical coarsening of inhomogeneous elastic materials We propose an approach for efficiently simulating elastic objects made of non-homogeneous, non-isotr...

Otros recursos de la mismacolección

  1. Inversion of the decay of the cyclotron line energy in Her X-1 Recent observations of Her X-1 with NuSTAR and INTEGRAL in 2016 have provided evidence that the 20-y...
  2. Hard X-ray Emission from the M87 AGN Detected with NuSTAR M87 hosts a 3-6 billion solar mass black hole with a remarkable relativistic jet that has been regul...
  3. Search for High-Energy Neutrinos from Binary Neutron Star Merger GW170817 with Antares, Icecube, and the Pierre Auger Observatory The Advanced LIGO and Advanced Virgo observatories recently discovered gravitational waves from a bi...
  4. On the Progenitor of Binary Neutron Star Merger GW170817 On August 17, 2017 the merger of two compact objects with masses consistent with two neutron stars w...
  5. GW170817: Implications for the Stochastic Gravitational-Wave Backgroud from Compact Binary Coalescences The LIGO Scientific and Virgo Collaborations have announced the first detection of gravitational wav...

Aviso de cookies: Usamos cookies propias y de terceros para mejorar nuestros servicios, para análisis estadístico y para mostrarle publicidad. Si continua navegando consideramos que acepta su uso en los términos establecidos en la Política de cookies.